added totalsegmentator task (#25)

* added totalsegmentator task

* Rename task and add more context to task description

---------

Co-authored-by: Leo <leo.misera@tu-dresden.de>
Co-authored-by: Georg Wölflein <georgw7777@gmail.com>

Author: 3 people

papers.bib

@@ -1,3 +1,14 @@
+@article{wasserthal2023totalsegmentator,
+  title={TotalSegmentator: robust segmentation of 104 anatomic structures in CT images},
+  author={Wasserthal, Jakob and Breit, Hanns-Christian and Meyer, Manfred T and Pradella, Maurice and Hinck, Daniel and Sauter, Alexander W and Heye, Tobias and Boll, Daniel T and Cyriac, Joshy and Yang, Shan and others},
+  journal={Radiology: Artificial Intelligence},
+  volume={5},
+  number={5},
+  pages={e230024},
+  year={2023},
+  publisher={Radiological Society of North America}
+}
+
 @article{isensee2020nnunet,
   author    = {Isensee,  Fabian and Jaeger,  Paul F. and Kohl,  Simon A. A. and Petersen,  Jens and Maier-Hein,  Klaus H.},
   title     = {nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation},

pyproject.toml

@@ -55,6 +55,7 @@ dev = [
 ]
 benchmark = [
     "h5py>=3.13.0",
+    "nibabel>=5.3.2",
 ]
 
 [tool.ruff.lint.per-file-ignores]

tasks/totalsegmentator_segment_liver/__init__.py

@@ -0,0 +1 @@
+# Add large files here that should not be committed to the repository

tasks/totalsegmentator_segment_liver/data/.gitignore

@@ -0,0 +1,5 @@
+The CT scans were downloaded from TCIA (https://www.cancerimagingarchive.net/collection/colorectal-liver-metastases/) and saved as .nii.gz.
+
+Citation: Simpson, A. L., Peoples, J., Creasy, J. M., Fichtinger, G., Gangai, N., Lasso, A., Keshava Murthy, K. N., Shia, J., D’Angelica, M. I., & Do, R. K. G. (2023). Preoperative CT and Survival Data for Patients Undergoing Resection of Colorectal Liver Metastases (Colorectal-Liver-Metastases) (Version 2) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/QXK2-QG03
+
+The original dataset is licensed under the CC BY 4.0 license. Modifications have been made to the original data during preprocessing.